1. Field of the Invention
This invention relates to an image processing method and apparatus for subjecting input image data to halftoning processing. More particularly, the invention relates to an image processing method and apparatus for halftoning input color image data based upon the algorithm of a discrete-time cellular neural network (DTCNN).
2. Description of the Related Art
Converting an analog signal of a natural image to a digital signal of a digital halftone image usually is carried out by discretization in the time direction (sampling) and in the magnitude direction (quantization). Such processing results in loss of information. However, if note is taken of the fact that a natural image contains many low-frequency components and exhibits strong correlation in a spatio-temporal neighborhood, a digital halftone image approximating the natural image can be obtained by quantization image processing involving a small number of bits. Quantization image processing involving a small number of bits is processing through which a digital halftone image expressed by a smaller number of bits is formed, by utilizing information in the spatio-temporal neighborhood area, from an analog natural image or from a quantized image consisting of a large number of bits obtained by A/D-converting each gray-level value of the analog natural image independently using an A/D converter that operates on a large number of bits.
The divided pixel digital halftoning has long been used to form a pseudo-digital halftone image. This method entails reproducing the grayscale by changing the percentage of black in a neighborhood image in order to reproduce a gray-level image by a black-and-white bi-level printer or display. Examples of such methods in practical use include the dither method, in which a gray level u(x,y) of the original image is compared with a threshold value T calculated in accordance with a set rule, and the error diffusion method, in which the error between an input gray-level image value and an output halftone image is diffused to pixels that have not yet been scanned.
A well-known technique for forming a full-color image involves halftoning input color image data to a small number of bits (e.g., single-bit bi-level data) using the error diffusion method and forming the full-color image using a bi-level printer or a bi-level display device.
However, in order to obtain a halftone image that approximates an analog natural image using the dither method, the number of bits per pixel must be made fairly large. A problem encountered with the error diffusion method is the blurring of images having sharp edges, such as character images that have been closely sampled. Another problem that arises when the number of bits per pixel is increased is the occurrence of a false contour which undergoes no change whatsoever only in a certain neighborhood.